The demand for high-resolution seasonal and climate change forecasts is continuously increasing in a variety of socio-economic impact sectors, including agriculture, energy, health, and insurance. To fill the gap between the coarse-resolution outputs available from Global Circulation Models (GCMs) and the regional needs of the impact applications used in the above sectors, a number of statistical downscaling techniques have been developed. Statistical downscaling is nowadays a mature and complex multi-disciplinary discipline involving a cascade of different scientific applications to access and process large amounts of heterogeneous data. Therefore, interactive user-friendly tools are necessary in order to ease the downscaling process for end users, thus maximizing the exploitation of the available predictions.

The Statistical Downscaling Portal (SD Portal) described in this paper has been designed following an end-to-end approach in order to transparently connect data providers and end users. To this aim, Internet and distributed computing technologies have been combined together with statistical tools to directly downscale GCM outputs to the regional or local scale required by impact applications. Thus, users can test and validate online di®erent methods (regression, neural networks, analogs, weather typing, etc.) using a Web browser, not worrying about the details of the techniques used or the different formats of the data accessed. The portal is part of the ENSEMBLES EU-funded project.